September 20, 2013
Why do scientists use Charts
and Graphs?
• visual representation of their results
• influence the public
a. visually driven society
b. when looking at a graph of experimental results,
always ask yourself if the researchers have an ulterior
motive
An Overview
Before conducting a meaningful investigation,
it's important to organize the data you
collected.
•
By organizing data, a scientist can more
easily interpret what has been observed.
•
Making sense of data is called
interpretation.
September 20, 2013
Data Tables and charts
Since most of the data scientist collect is
quantitative, data tables and charts are usually used
to organize the information
• Graphs are created from data tables
• They allow the investigator to get a visual image
of the observations, which simplifies interpretation
and drawing conclusions
• Valid conclusions depend on organization and
clear interpretation of data.
Data Tables
When creating data tables, place the manipulated variable
in the left column and the responding variable in the right
column.
• Create a table with the following information
September 20, 2013
Column (Bar) Charts
· always adds up to 100%
· used to show how some fixed
amount/quality is broken down
amounts
· used to compare
how students spend their day
· ex.
· NEVER use horizontal bars...ALWAYS vertical
· ex. show the # and type of birds seen at Oak
Park
Circle (Pie) Charts
· always adds up to 100%
· used to show how some fixed amount/quantity is
broken down
· ex. how students spend their day
September 20, 2013
Line Graphs
· used to show trends or how data changes
over time
· ex. growth of plant A over 10 days
compared to the growth of plant B over
the same time period
Types of graphs
Two types of graphs are typically used when
organizing scientific data...
• Descriptive data requires a bar chart or pie chart
and has data that comes from research
questions asking variables that will be counted.
September 20, 2013
How to make a bar graph:
1. Use an appropriate scale and a reasonable
starting point for each axis.
2. Label the axes, and plot the data
3. Choose a title that accurately represents the
data.
Use the data below to create a bar graph
September 20, 2013
Continuous data requires a line graph. This type of
data comes from research questions that ask about
variables being investigated over time.
• Because the year and the population change, they
are the variables. The population is determined by,
or dependent on, the year. So population is the
dependent variable, and the year is the
independent variable.
• Each set of data is called a data pair. Data pairs are
easily organized into data tables.
September 20, 2013
How to make a line graph
1. Label the x axis (horizontal axis) with the independent
variable.
2. Label the y-axis (vertical axis) with the dependent
variable.
3. Determine the range of your data that must fit on each
axis. The range will set the scale.
4. Number each axis division (line). Each division should
be equally spaced.
5. Plot each data pair accurately as a point on the graph.
6. Choose a title that describes the graph.
Distance from the sun
(AU)
0.39
0.72
1.0
1.5
5.2
Surface Temperature
(℃)
327
482
14
-23
-151
9.6
-184
19.2
-207
30.1
-223
September 20, 2013
How to determine slope.
Slope is the ratio of the change in the y-value to the
change in the x-value. It is sometimes called the rise
over the run.
1.
Choose two points (A and B)
on the line graph.
2. Find the change in the y value
(YB-YA).
3. Find the change in the x value.
(XB-XA).
4. Divide the change in x by the
change in y.
September 20, 2013
Interpreting data
The final step of the investigation is to draw conclusions and
interpret the data.
• A conclusion is a factual summary of data. Usually
more than one conclusion statement is required to
summarize a data set.
• An interpretation is a generalization that explains or
interprets the data set.
Below is data from an investigation that measured the
absorbancy of three types of paper towels.
conclusion: Towel A absorbed an average of 27 mL of
water. Towel B absorbed an average of 24.5 mL of
water while towel C absorbed an average of 20.5 mL of
water
inference: Towel A is the most absorbent and towel C
the least absorbent.
September 20, 2013
For homework 1.6 graphing data
Make a data table
Make a chart/graph
Use color in your charts and graphs
SULTAN